Research and development of general technical specifications for video surveillance systems in the coal mining industry
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摘要:
为提升煤矿工业视频监控系统在现代化矿井复杂应用场景下的环境适应性、智能分析可靠性，除图像监视功能外，系统应增加：① 视频图像质量自诊断机制，对视频图像质量和云台镜头远程控制的有效性进行自动检测和诊断。② 多层级智能视频分析（IVA）体系，包括目标检测、目标识别、行为识别、事件检测等。③ 可配置IVA框架，支持根据需求选择和配置IVA功能。④ 结构化视频描述与索引，支持对IVA结果进行自动描述，以及基于IVA结果等信息建立索引。⑤ 跨系统报警联动，具备报警联动数据交互接口，发送IVA结果等信息至其他设备或系统。系统主要IVA功能应通过最大误差、误报率、漏报率、IVA延迟等指标进行量化，其中最大误报率不高于5%，漏报率不高于10%，IVA延迟不大于2 s。设计多场景模拟试验综合验证系统性能，主要包括：① 采用视频质量干扰模拟与主观评价机制验证视频图像质量自诊断功能和系统图像质量。② 构建测试视频导入、测试视频翻拍、场景模拟三重测试体系评估IVA功能。③ 采用总带宽占用量计算或最大数量视频信号接入测试方式验证系统最大容量。
Abstract:To enhance the environmental adaptability and reliability of intelligent analysis of video surveillance systems in the coal mining industry under complex modern mine scenarios, in addition to image monitoring functions, the system should include: ① a video image quality self-diagnosis mechanism that automatically detects and diagnoses the quality of video images and the effectiveness of remote control of the PTZ lens. ② a multi-level Intelligent Video Analysis (IVA) system, including target detection, target recognition, behavior recognition, and event detection. ③ a configurable IVA framework that supports selecting and configuring IVA functions according to needs. ④ structured video description and indexing, supporting automatic description of IVA results and the establishment of indexes based on IVA results and related information. ⑤ cross-system alarm linkage, equipped with data interaction interfaces for alarm linkage, sending IVA results and other information to other devices or systems. The main IVA functions of the system should be quantitatively evaluated by indicators such as maximum error, false alarm rate, missed detection rate, and IVA latency, with the maximum false alarm rate not exceeding 5%, missed detection rate not exceeding 10%, and IVA latency not exceeding 2 seconds. Design multi-scenario simulation tests to comprehensively verify system performance, mainly including: ① verification of video image quality self-diagnosis function and system image quality through video quality interference simulation and subjective evaluation mechanisms. ② evaluation of IVA functions by establishing a triple test system including test video import, test video re-shooting, and scenario simulation. ③ verification of system maximum capacity by total bandwidth occupancy calculation or maximum number of video signal access tests.
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图 3 系统作为其他主系统或装置子系统时的拓扑方式
Figure 3. Topology of a system functioning as a subsystem within a main system or device
表 1 目标检测功能主要技术指标
Table 1 Key technical indicators of object detection function
功能 技术指标 掘进工作面、采煤工作面、主运
输系统巷道和煤仓内人员计数最大误差≤±1人（当画面中同时出现人
数不超过15人时），Tlatency≤1 s钻杆动态计数 最大误差≤±1根（钻杆数量少于50根时）
或≤±2根（钻杆数量超过50根时），
Tlatency≤1 s刮板输送机大块煤检测 FNR≤2%，FPR≤10%，Tlatency≤1 s 胶带目标状态检测 FNR≤2%，FPR≤10%，Tlatency≤1 s 辅助运输车辆速度检测 最大误差≤±10%，Tlatency≤0.5 s 经过路口辅助运输车辆计数 最大误差≤±1辆（每经过100辆），Tlatency≤1 s 井底积煤检测 最大误差≤5 cm，覆盖井底的积煤区域≥95%，FNR≤2%，FPR≤10%，Tlatency≤1 s 箕斗煤残留检测 最大误差≤5 cm，覆盖箕斗区域≥95%，FNR≤2%，FPR≤10%，Tlatency≤1 s 选煤厂胶带撒料检测 FNR≤2%，FPR≤10%，Tlatency≤1 s 选煤厂刮板输送机断链检测 FNR≤2%，FPR≤10%，Tlatency≤0.5 s 
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表 2 目标识别功能主要技术指标
Table 2 Key technical indicators of target recognition function
功能 技术指标 关键工序识别 FNR≤5%，FPR≤10%，Tlatency≤1 s 设备运行状态识别 FNR≤3%，FPR≤10%，Tlatency≤2 s 信号灯、人员状态、车辆状态、
人车相对状态识别FNR≤2%，FPR≤5%，Tlatency≤0.5 s 防跑车装置状态识别 FNR≤1%，FPR≤5%，Tlatency≤1 s 钢丝绳外观缺陷检测 FNR≤2%，FPR≤8%，Tlatency≤2 s 井筒渗水、螺栓脱落、
电缆卡子脱落检测FNR≤2%，FPR≤8%，Tlatency≤2 s 风门状态识别 FNR≤2%，FPR≤5%，Tlatency≤2 s
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表 3 行为识别功能主要技术指标
Table 3 Key technical indicators of behavior recognition function
功能 技术指标 人员闯入警戒区域监测 FNR≤2%，FPR≤5%，Tlatency≤1 s 人员吸烟检测 FNR≤5%，FPR≤10%，Tlatency≤1 s 人员班中脱岗、睡岗检测 FNR≤3%，FPR≤8%，Tlatency≤5 s 人员未佩戴安全帽检测 FNR≤2%，FPR≤5%，Tlatency≤1 s 人员未佩戴口罩检测 FNR≤4%，FPR≤8%，Tlatency≤2 s 人员乘坐架空乘人装置时携带大件物品检测 FNR≤2%，FPR≤6%，Tlatency≤2 s 人员在轨道上逗留徘徊、多人并行检测 FNR≤3%，FPR≤8%，Tlatency≤2 s 人员未佩戴自救器、矿灯及跨越胶带、乘坐胶
带检测，登高作业人员未佩戴安全绳检测FNR≤2%，FPR≤5%，Tlatency≤1 s 人员违规作业识别 FNR≤3%，FPR≤8%，Tlatency≤2 s 电工穿戴不合规识别 FNR≤2%，FPR≤5%，Tlatency≤1 s
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表 4 事件检测功能主要技术指标
Table 4 Key technical metrics for event detection
功能 技术指标 工作面或选煤厂刮板输送机故障检测 FNR≤2%，FPR≤5%，Tlatency≤1 s 提升机尾绳异常检测 FNR≤2%，FPR≤6%，Tlatency≤1 s 辅助运输车辆顶撞风门检测 FNR≤2%，FPR≤5%，Tlatency≤1 s
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表 5 主观评价指标评分
Table 5 Subjective evaluation indicators rating scale
得分 5 4 3 2 1 目标
辨识度目标清晰，
完全可辨识目标清晰，
可辨识目标部分清晰，
但仍可辨识目标
不清晰目标
不可辨识
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